Integration of simulated and observed states through data assimilation as well as model evaluation requires
a realistic representation of soil moisture in land surface models (LSMs). However, soil moisture in LSMs is
sensitive to a range of uncertain input parameters, and intermodel differences in parameter values are often
large. Here, we investigate the effect of soil parameters on soil moisture and evapotranspiration by using
parameters from three different LSMs participating in the European Land Data Assimilation System
(ELDAS) project. To prevent compensating effects from other than soil parameters, the effects are evaluated
within a common framework of parsimonious stochastic soil moisture models. First, soil parameters are
shown to affect soil moisture more strongly than the average evapotranspiration. In arid climates, the effect
of soil parameters is on the variance rather than the mean, and the intermodel flux differences are smallest.
Soil parameters from the ELDAS LSMs differ strongly, most notably in the available moisture content
between the wilting point and the critical moisture content, which differs by a factor of 3. The ELDAS
parameters can lead to differences in mean volumetric soil moisture as high as 0.10, and an average
evapotranspiration of 10%–20% for the investigated parameter range. The parsimonious framework presented
here can be used to investigate first-order parameter sensitivities under a range of climate conditions
without using full LSM simulations. The results are consistent with many other studies using different LSMs
under a more limited range of possible forcing conditions.